“It would allow vehicle charging to be very similar to filling up at the gas station.”
If made widely available, it could help the UK Government achieve its target of ending the sale of petrol and diesel cars by 2030.
Charging the lithium-ion batteries that fuel electric vehicles is a delicate balancing act. Ideally, drivers want to power up as quickly as possible to get back on the road, but with current technology, speeding up the process can cause damage.
When a lithium-ion battery is being charged, lithium ions migrate from one side of the device, the cathode, to the other, the anode.
By making the lithium ions migrate faster, the battery is charged more quickly, but sometimes the lithium ions don’t fully move into the anode.
In this situation, lithium metal can build up, and this can trigger early battery failure. It can also cause the cathode to wear and crack.
All of these issues reduce the lifetime of the battery and the effective range of the vehicle.
Speeding up the charge while avoiding the damage requires a huge amount of data on how it affects devices’ lifetimes, efficiencies and safety.
It is also important to take into account the design and condition of batteries, as well as how the charging method would fit into the electric grid infrastructure.
Dr. Dufek and colleagues sought to address this by using machine learning techniques that analyze charging data to create unique charging methods.
By inputting information about the condition of many lithium-ion batteries during their charging and discharging cycles, the scientists trained the machine learning analysis to predict lifetimes and the ways that different designs would eventually fail.
The team then fed that data back into the analysis to identify and optimize new methods that they then tested on real batteries.
Dr. Dufek added: “We’ve significantly increased the amount of energy that can go into a battery cell in a short amount of time.
“Currently, we’re seeing batteries charge to over 90 percent in 10 minutes without lithium plating or cathode cracking.”
The development is a large advance on current methods, the best of which can fully charge an electric vehicle in about 30 minutes.
While many researchers are looking for methods to achieve super-fast charging, Dr. Dufek said that one advantage of their machine learning model is that it ties the charging methods to the physics of what is actually happening in a battery.
Now, the researchers plan to use their model to develop better methods and to help design new lithium-ion batteries that are designed for fast charging.
The ultimate goal, they say, is for electric vehicles to be able to tell charging stations how to power up their specific batteries quickly and safely.
Stories and infographics by ‘Talker Research’ are available to download & ready to use. Stories and videos by ‘Talker News’ are managed by SWNS. To license content for editorial or commercial use and to see the full scope of SWNS content, please email [email protected] or submit an inquiry via our contact form.
We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. By clicking “Accept All”, you consent to the use of ALL the cookies. However, you may visit "Cookie Settings" to provide a controlled consent.
This website uses cookies to improve your experience while you navigate through the website. Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may affect your browsing experience.
Necessary cookies are absolutely essential for the website to function properly. These cookies ensure basic functionalities and security features of the website, anonymously.
Cookie
Duration
Description
cookielawinfo-checkbox-analytics
11 months
This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics".
cookielawinfo-checkbox-functional
11 months
The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional".
cookielawinfo-checkbox-necessary
11 months
This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary".
cookielawinfo-checkbox-others
11 months
This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other.
cookielawinfo-checkbox-performance
11 months
This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance".
viewed_cookie_policy
11 months
The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. It does not store any personal data.
Functional cookies help to perform certain functionalities like sharing the content of the website on social media platforms, collect feedbacks, and other third-party features.
Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.
Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc.
Advertisement cookies are used to provide visitors with relevant ads and marketing campaigns. These cookies track visitors across websites and collect information to provide customized ads.